About the Course
Organizations want data results they can prove: faster access to trusted data, clearer decision rights, better governance, stronger analytics delivery, and more visible value from data investment. In this field, credibility depends on how well you can connect the operating model to real business outcomes, not on how well you can describe aspirations. A practical design effort usually draws on the Galbraith Star Model, target operating model thinking, and data governance structures that clarify accountability, funding, and service expectations.
This course turns scattered knowledge into a structured system for data strategy and operating model design. You will practice building a capability map, defining decision rights, mapping governance forums, drafting a data operating model blueprint, and shaping a roadmap that sequences change into manageable releases. You will also be introduced to how AI-assisted metadata management, automated data quality monitoring, and digital collaboration tools are changing how data teams operate, but the main focus stays on operational design rather than tool engineering. This course teaches you how to assess the current state, design a future-state operating model, and prepare implementation materials that leadership can review and sponsor.
Real delivery constraints matter in this domain: budget pressure, competing digital priorities, uneven data maturity, and fragmented ownership across business and technology teams. The course is built for professionals who must design a credible data operating model while balancing governance burden, delivery capacity, and stakeholder expectations. This means you will work with practical templates and scenario-based exercises that reflect the trade-offs common in enterprise data transformation, not idealized textbook conditions.
Target Audience
This course is designed for professionals who shape data priorities, govern enterprise information flows, and turn strategy into an operating model that can be executed across business and technology teams.
- Data Strategy Leads defining enterprise capability priorities and sequencing
- Data Governance Managers clarifying decision rights and stewardship accountability
- Enterprise Data Architects aligning data capabilities with target operating model design
- Analytics Managers improving service models for reporting and insight delivery
- Chief Data Officers coordinating governance, funding, and business value realization
- Data Operations Managers managing intake, issue resolution, and data service routines
- Business Information Managers linking data services to business process needs
- Transformation Managers integrating operating model changes into wider change portfolios
- Master Data Management Specialists supporting ownership, standards, and control points
- Information Management Consultants shaping practical blueprints and roadmap deliverables
Course Objectives
This course equips you to plan, execute, and measure data strategy and operating model design initiatives that improve governance clarity, implementation readiness, and strategic alignment.
- Assess current-state data capabilities using a capability map and Galbraith Star Model lens.
- Apply target operating model design methods to a data strategy and governance challenge.
- Design a data operating model blueprint with decision rights, forums, and service boundaries.
- Construct a capability roadmap that sequences governance, architecture, and data quality improvements.
- Evaluate operating model gaps against COBIT and data governance accountability expectations.
- Navigate stakeholder dependencies across business owners, data stewards, and technology teams.
- Implement measurable data KPIs and operating metrics using digital dashboard workflows.
- Synthesize findings into an executive briefing, roadmap, and operating model narrative.
Requirements & Prerequisites
Participants should have working knowledge of data management, analytics, or enterprise technology environments. Familiarity with operating model concepts, governance forums, or transformation planning will help you move faster, but no coding or programming is required. The course is taught at an intermediate level, and the advanced content is presented at an operational design level, not at technical engineering depth.
Professional and Organizational Impact
When you lead data strategy and operating model design with credible data and practical strategies, you become a trusted driver of governance clarity and execution discipline.
- Build confidence in mapping capabilities to outcomes and ownership.
- Gain stronger fluency in target operating model design for data functions.
- Strengthen your ability to balance governance controls with delivery speed.
- Enhance your use of decision-right matrices and capability maps.
- Develop practical skill in drafting data roadmap and blueprint artefacts.
- Position yourself as a credible bridge between business, data, and technology teams.
- Expand your influence in enterprise data transformation and operating model work.
- Improve your readiness to speak to leaders using measurable operating metrics.
Organizations that embed data strategy and operating model design into enterprise change reduce costs, mitigate risks, and build lasting competitive advantage.
- Reduce duplication by clarifying ownership across data domains.
- Lower governance friction through clearer decision rights and escalation paths.
- Improve trust in reporting by standardizing stewardship and quality controls.
- Accelerate transformation delivery by sequencing data capabilities realistically.
- Reduce remediation costs by surfacing operating model gaps earlier.
- Strengthen regulatory and audit readiness through defined accountability structures.
- Improve executive visibility into data investment priorities and value realization.
- Support market positioning through faster, more reliable data-enabled decisions.
Training Methodology
This is a practical, outcome-driven course designed to turn data strategy and operating model design aspiration into measurable action and credible reporting.
Methodology includes:
- Hands-on capability scoring using a data maturity diagnostic spreadsheet and KPI baseline.
- Scenario simulation for a funding constraint case where data priorities must be sequenced.
- Assessment exercise using a target operating model checklist and governance gap analysis.
- Stakeholder mapping workshop for data owners, stewards, CDO office, and architecture forums.
- Case study analysis across financial services, healthcare, manufacturing, and public sector data functions.
- Group workshop to produce a data operating model blueprint and 12-month roadmap.
- Reflection exercise comparing current governance routines against COBIT and operating metric benchmarks.
Upcoming Sessions
Next available dates worldwide
No international sessions scheduled
Certification
Recognized credentials that advance your career
Participants who complete the Data Strategy and Operating Model Design Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Effective Learning & Skill Development
- Build expertise with structured, outcome-driven learning.
- Equip individuals and teams with skills that grow with industry needs.
- Reinforce learning through real-world scenarios, case studies and practical exercises.
Career Growth & Professional Advancement
- Apply what you learn with a proven methodology that ensures lasting impact.
- Develop immediately usable skills that translate directly into workplace success.
- Gain the expertise needed for career advancement and leadership roles.
Training Optimization & Learning Excellence
- Tailor training to industry-specific challenges and organizational goals.
- Use data-driven insights and automation to enhance training effectiveness.
- Evaluate progress and ensure long-term learning success.
